We combine a weighted finite state transducer (WFST)-based decoder with the Conformer encoder in order to utilize an expanded lexicon and n-gram language model. For our experiments, we use trigram LMs.
This has been done before in [1]}[2]}, and in particular our approach is similar to WFST decoding in [2]} using a decoder implemented in Kaldi [4]}.
The WFST is a simple composition of three transducers: a token transducer, which removes blank symbols output by CTC and collapses repeated characters; a lexicon transducer, which maps sequences of collapsed characters into words; and a grammar transducer, which contains the n-gram LM.
